Home // ADAPTIVE 2025, The Seventeenth International Conference on Adaptive and Self-Adaptive Systems and Applications // View article
Authors:
Mohammed Fahad Ali
Dominique Fabio Briechle
Marit Elke Anke Briechle-Mathiszig
Thomas Tobias Marcello Geger
Andreas Rausch
Keywords: Bicycles; Repairing; Product-Service-System; Artificial Intelligence; Circular Economy.
Abstract:
Bicycles play an essential role in today’s mobility ecosystems and are an important part of future mobility concepts. Bicycles develop defects as a result of frequent use both during and after the operational phase. In some cases, repairing can be a solution to prolong the duration of a bicycle’s usage by restoring its condition while simultaneously preventing the generation of new waste. To plan the repair process, it is critical for both the bicycle’s owner, referred to as the client, and the repair service provider to determine the defects and whether fixing the problem is worthwhile in this particular situation. Therefore, there is currently a gap in potential solutions for accelerating this process. The paper aims to investigate how Artificial Intelligence (AI) can support repair business models to increase the attractiveness of sustainable, prolonged solutions. Consequently, AI-based experiments were conducted to design two specific classifiers with the aim of examining the state of different kinds of bicycles. The AI-based models were trained, validated, and tested in these experiments to develop a product-service-system based on the images of the bicycles and the repair information collected from the repair service provider.
Pages: 16 to 23
Copyright: Copyright (c) IARIA, 2025
Publication date: April 6, 2025
Published in: conference
ISSN: 2308-4146
ISBN: 978-1-68558-261-6
Location: Valencia, Spain
Dates: from April 6, 2025 to April 10, 2025